• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.679-684
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• 2002

MODIS LAI has been one of key products for analyzing the quantitative aspects ofterrestrial ecology. This study was designed to validate MODIS LAS product by using the reference LAI map that was derived from both ground measurements and ETM＋ surface reflectance. The study area, the Kwangneung Experiment Forest in Korea, covers mixed species of deciduous and conifers of temperate forest. Throughout the growing season of 2002, we have measured LAS at the 30 sample plots using an optical device. Ground measured LAS data were then correlated to the ETM＋ reflectance to produce a continuous map of LAS over the study area. Preliminary comparison between MODIS LAI and the reference LAI map showed the lower LAI values from the MODIS product.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.371-380
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• 2003

The primary objective of this study is to develop a suitable methodology to generate forest leaf area index (LAI) map at regional and local scales. To build empirical models, we collected the LAI values at 30 sample plots over the forest within the kyongan watershed area by the field measurements using an optical instrument. Landsat-7 ETM＋ multispectral data obtained at the same growing season with the field LAI measurement were used. Three datasets of remote sensing signal were prepared for analyzing the relationship with the field measured LAI value and they include raw DN, atmospherically corrected reflectance, and topographically corrected reflectance. From the correlation analysis and regression model development, we found that the radiometric correction of topographic effects was very critical step to increase the sensitivity of the multispectral reflectance to LAI. In addition, the empirical model to generate forest LAI map should be separately developed for each of coniferous and deciduous forest.

• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.132-137
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• 2010

Site-specific N application for corn is one of the precision crop management. To implement the site-specific N application, various nitrogen stress sensing methods, including aerial image, tissue analysis, soil sampling analysis, and SPAD meter readings, have been used. Use of side-dressing, an efficient nitrogen application method than a uniform application in either late fall or early spring, relies mainly on the capability of nitrogen deficiency detection. This paper presents map-based variable rate nitrogen application based using a multi-spectral corn nitrogen deficiency(CND) sensor. This sensor assess the nitrogen stress by means of the estimated SPAD reading calculated from the corn leave reflectance. The estimated SPAD value from the CND sensor system and location information form DGPS of each field block was combined into the field map using a ArcView program. Then this map was converted into a raster file for a map-based variable rate application software. The relative SPAD (RSPAD = SPAD over reference SPAD) was investigated 2 weeks after the treatments. The results showed that the map-based variable rate application system was feasible.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.2 s.8
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• pp.35-45
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• 1996

The reflectance of chlorophyll was measured using UV-VIS spectrophotometer with the reflectance integrator in the laboratory in order to define its spectral characteristics. Sharp peaks appear at around 485nm and 655nm due to fluorescence and scattering, and the reflectance of chlorophyll increases at 580nm. With the increase in the chlorophyll concentration, the reflectance also increases. We have applied TM data to the reflectance spectrum of chlorophyll and have developed two formula with which one can estimate the chlorophyll concetration. Satellite re sensing, with its synoptic overage, is used to obtain the chlorophyll concentration in Daecheong reservoir. The approach involved acquisition of water quality samples front boat simultaneous with Landsat 5 satellite overpass. The remotely-sensed data and the ground truth data were obtained oil 20 June 1995 and on 18 March 1996. Regression models have been developed between the chlorophyll concentration and Landsat Thematic Mapper digital data. As the regression model was determined based on the correlation coefficient which was higher than 0.7 and the spectral characteristics of chlorophyll, and we have applied it to the entire study area to genelate a distribution map of trophic state. According to the trophic state map made based upon Aizaki's TSI and chlorophyll a concentration, the area where Okchun stream was flowing into was shown to be polluted the most all over the Daechung reservoir by showing an eutrophic state in June 1995 and a mesotrophic state in March 1996.

• Journal of Biosystems Engineering
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• v.36 no.3
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• pp.180-186
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• 2011

The objective of this research was to establish the estimation method of growth information on potato using Multi-Spectral Image Sensor (MSIS) and Global Positioning System (GPS). And growth estimation map for determining a prescription map over the entire field was generated. To determine the growth model, 10 ground-truth points of areas of $4m^2$ each were selected and investigated. The growth information included stem number, crop height and SPAD value. In addition, images information involving the ground-truth points were also taken by an unmanned helicopter, and reflectance value of Green, Red, and NIR bands were calculated with image processing. Then, growth status of potato was modeled by multi-regression analysis using these reflectance value of Green, Red, and NIR. As a result, potato growth information could be detected by analyzing Green, Red, and NIR images. Stem number, crop height and SPAD value could be estimated with $R^2$ values of 0.600, 0.657 and 0.747 respectively. The generated GIS map would describe variability of the potato growth in a whole field.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.259-266
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• 2002

It is crucial to know spatial soil variability for precision farming. However, it is time-consuming, and difficult to measure spatial soil properties. Therefore, there are needs fur sensing technology to estimate spatial soil variability, and for electronic mapping technology to store, manipulate and process the sampled data. This research was conducted to develop a real-time soil organic matter sensor and an electronic mapping system. A soil organic matter sensor was developed with a spectrophotometer in the 900∼1,700 nm range. It was designed in a penetrator type to measure reflectance of soil at 15cm depth. The signal was calibrated with organic matter content (OMC) of the soil which was sampled in the field. The OMC was measured by the Walkeley-Black method. The soil OMCs were ranged from 0.07 to 7.96%. Statistical partial least square and principle component regression analyses were used as calibration methods. Coefficient of determination, standard error prediction and bias were 0.85 0.72 and -0.13, respectively. The electronic mapping system was consisted of the soil OMC sensor, a DGPS, a database and a makeshift vehicle. An algorithm was developed to acquire data on sampling position and its OMC and to store the data in the database. Fifty samples in fields were taken to make an N-fertilizer dosage map. Mean absolute error of these data was 0.59. The Kring method was used to interpolate data between sampling nodes. The interpolated data was used to make a soil OMC map. Also an N-fertilizer dosage map was drawn using the soil OMC map. The N-fertilizer dosage was determined by the fertilizing equation recommended by National Institute of Agricultural Science and Technology in Korea. Use of the N-fertilizer dosage map would increase precision fertilization up to 91% compared with conventional fertilization. Therefore, the developed electronic mapping system was feasible to not only precision determination of N-fertilizer dosage, but also reduction of environmental pollution.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.77-84
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• 2008

This paper proposes a new approach to eliminate the reflectance component for the localization of text in natural scene images. Natural scene images normally have an illumination component as well as a reflectance component. It is well known that a reflectance component usually obstructs the task of detecting and recognizing objects like texts in the scene, since it blurs out an overall image. We have developed an approach that efficiently removes reflectance components while Preserving illumination components. We decided whether an input image hits Normal or Polarized for determining the light environment, using the histogram which consisted of a red component. In the normal image, we acquired the text region without additional processing. Otherwise we removed light reflecting from the object using homomorphic filtering in the polarized image. And then this decided the each text region based on the color merging technique and the Saliency Map. Finally, we localized text region on these two candidate regions.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.227-236
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• 1997

Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.378-381
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• 2002

We retrieved the aerosol optical thickness $\tau$$_{a}$ over land from Landsat-7/ETM+ image data using the correlation between the visible reflectance and middle IR reflectance. This band correlation method for aerosol retrieval was originally proposed fur MODIS data analysis by Kaufman et al.(1977). The results of retrieved aerosol optical thickness $\tau$$_{a}$ from Landsat-7/ETM+ data were compared with the simultaneous sky observation data at our study site. We found a good agreement between the retrieved and observed values. We presented the distribution maps of the aerosol optical thickness over land, retrieved from Landsat-7/ETM+ image data. Then, the surface reflectance map was also presented. The aerosol optical thickness over sea was retrieved assuming no reflected contribution from sea in the near IR band. In addition, we discussed some limitations when we apply the band correlation method.

• Korean Journal of Remote Sensing
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• v.19 no.1
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• pp.1-9
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• 2003

MODIS LAI product has been one of key variable for analyzing the quantitative aspects of terrestrial ecology at global scale. This study was designed to validate MODIS global LAI product for regional application. To examine the quality of MODIS LAI data, we developed a reference LAI surface that was derived by relating the ground LAI measurements to Landsat ETM+ reflectance. The study area, the Kwangneung Experiment Forest in Korea, covers mixed deciduous and coniferous species of temperate forest. Ground measurements of LAI were conducted at 30 sample plots by using a photo-optical instrument during the growing season of 2002. Ground measured LAI data were then related to the ETM+ reflectance to produce a continuous map of LAI surface over the study area. From the comparison between the MODIS LAI and the reference LAI, it was found that the MODIS LAI values were slightly higher at the forestland. Considering the limitations of producing the reference LAI surface and the uncertainty of the input variable for the MODIS LAI algorithm, such small discrepancy mal not be significant.